anko-intel commented on a change in pull request #20713: URL: https://github.com/apache/incubator-mxnet/pull/20713#discussion_r786618910
########## File path: src/operator/nn/dnnl/dnnl_binary.cc ########## @@ -0,0 +1,78 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +/*! + * \file dnnl_binary.cc + * \author: Adam Grabowski, [email protected] + */ + +#if MXNET_USE_ONEDNN == 1 +#include "./dnnl_binary-inl.h" + +namespace mxnet { +namespace op { + +DNNLBinaryOpFwd::DNNLBinaryOpFwd(const dnnl::algorithm alg, + const std::vector<NDArray>& inputs, + const std::vector<NDArray>& outputs) { + auto src0_desc = inputs[0].GetDNNLData()->get_desc(); + auto src1_desc = inputs[1].GetDNNLData()->get_desc(); + auto dst_desc = outputs[0].GetDNNLData()->get_desc(); + + dnnl::binary::desc fwd_desc(alg, src0_desc, src1_desc, dst_desc); + fwd_pd = std::make_shared<binary_fwd_pd_t>(fwd_desc, mxnet::CpuEngine::Get()->get_engine()); + fwd = std::make_shared<binary_fwd_t>(*fwd_pd); +} + +void DNNLBinaryOpFwd::Execute(const std::vector<NDArray>& inputs, + const std::vector<OpReqType>& req, + const std::vector<NDArray>& outputs) { + auto engine = mxnet::CpuEngine::Get()->get_engine(); + auto src0 = inputs[0].GetDNNLData(); + auto src1 = inputs[1].GetDNNLData(); + dnnl_output_t out_mem; + if (outputs[0].GetDNNLData()->get_data_handle() == inputs[1].GetDNNLData()->get_data_handle()) + out_mem = CreateDNNLMem(outputs[0], fwd_pd->dst_desc(), req[0], &inputs[1]); + else + out_mem = CreateDNNLMem(outputs[0], fwd_pd->dst_desc(), req[0], &inputs[0]); + + dnnl_args_map_t args = { + {DNNL_ARG_SRC_0, *src0}, + {DNNL_ARG_SRC_1, *src1}, + {DNNL_ARG_DST, *out_mem.second}, + }; + + DNNLStream::Get()->RegisterPrimArgs(*fwd, args); + CommitOutput(outputs[0], out_mem); + DNNLStream::Get()->Submit(); +} + +bool SupportDNNLBinary(const std::vector<NDArray>& inputs) { + auto dtype = inputs[0].dtype(); + auto ndim_0 = inputs[0].shape().ndim(); + auto ndim_1 = inputs[1].shape().ndim(); + return ndim_0 >= 1 && ndim_0 <= 6 && ndim_1 >= 1 && ndim_1 <= 6 && + inputs[0].shape().Size() != 0 && inputs[1].shape().Size() != 0 && + dtype == mshadow::kFloat32 && dtype == inputs[1].dtype(); Review comment: please check if oneDNN supports bfloat, if yes please create separate PR for it. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
